---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- Anthropic/hh-rlhf
---

[Pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) supervised finetuned using TRLx library with the helpful subset of [Anthropic-hh-rlhf dataset](https://huggingface.co/datasets/Anthropic/hh-rlhf) for 1 epoch. 

Checkpoints are also uploaded. 

Fully reproducible finetuning code is available on [GitHub](https://github.com/lauraaisling/trlx-pythia/tree/main)

[wandb log](https://wandb.ai/lauraomahony999/pythia-sft/runs/9507tygf)

See [Pythia-160m](https://huggingface.co/EleutherAI/pythia-410m) for model details [(paper)](https://arxiv.org/abs/2101.00027). 

See further details of these models in the paper [Attributing Mode Collapse in the Fine-Tuning of Large Language Models](https://openreview.net/pdf?id=3pDMYjpOxk).

You can cite these models if they are helpful as follows: 

<pre>
@inproceedings{o2024attributing,
  title={Attributing Mode Collapse in the Fine-Tuning of Large Language Models},
  author={O’Mahony, Laura and Grinsztajn, Leo and Schoelkopf, Hailey and Biderman, Stella},
  booktitle={ICLR 2024, Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) workshop},
  year={2024}
}
</pre>

hf (pretrained=lomahony/pythia-160m-helpful-sft), gen_kwargs: (None), limit: None, num_fewshot: 0, batch_size: 16
|    Tasks     |Version|Filter|n-shot|    Metric     | Value  |   |Stderr |
|--------------|------:|------|-----:|---------------|-------:|---|-------|
|arc_challenge |      1|none  |     0|acc            |  0.1894|±  | 0.0115|
|              |       |none  |     0|acc_norm       |  0.2235|±  | 0.0122|
|arc_easy      |      1|none  |     0|acc            |  0.3889|±  | 0.0100|
|              |       |none  |     0|acc_norm       |  0.3737|±  | 0.0099|
|boolq         |      2|none  |     0|acc            |  0.5346|±  | 0.0087|
|hellaswag     |      1|none  |     0|acc            |  0.2801|±  | 0.0045|
|              |       |none  |     0|acc_norm       |  0.2949|±  | 0.0046|
|lambada_openai|      1|none  |     0|perplexity     |439.3682|±  |23.5771|
|              |       |none  |     0|acc            |  0.0984|±  | 0.0041|
|openbookqa    |      1|none  |     0|acc            |  0.1580|±  | 0.0163|
|              |       |none  |     0|acc_norm       |  0.2260|±  | 0.0187|
|piqa          |      1|none  |     0|acc            |  0.5936|±  | 0.0115|
|              |       |none  |     0|acc_norm       |  0.5865|±  | 0.0115|
|sciq          |      1|none  |     0|acc            |  0.5710|±  | 0.0157|
|              |       |none  |     0|acc_norm       |  0.6290|±  | 0.0153|
|wikitext      |      2|none  |     0|word_perplexity| 87.3261|±  |N/A    |
|              |       |none  |     0|byte_perplexity|  2.3068|±  |N/A    |
|              |       |none  |     0|bits_per_byte  |  1.2059|±  |N/A    |
|winogrande    |      1|none  |     0|acc            |  0.4878|±  | 0.0140|

hf (pretrained=lomahony/pythia-160m-helpful-sft), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 16
|    Tasks     |Version|Filter|n-shot|    Metric     |  Value  |   |Stderr |
|--------------|------:|------|-----:|---------------|--------:|---|-------|
|arc_challenge |      1|none  |     5|acc            |   0.2022|±  | 0.0117|
|              |       |none  |     5|acc_norm       |   0.2270|±  | 0.0122|
|arc_easy      |      1|none  |     5|acc            |   0.3733|±  | 0.0099|
|              |       |none  |     5|acc_norm       |   0.3746|±  | 0.0099|
|boolq         |      2|none  |     5|acc            |   0.5413|±  | 0.0087|
|hellaswag     |      1|none  |     5|acc            |   0.2770|±  | 0.0045|
|              |       |none  |     5|acc_norm       |   0.2853|±  | 0.0045|
|lambada_openai|      1|none  |     5|perplexity     |1644.8526|±  |87.8870|
|              |       |none  |     5|acc            |   0.0491|±  | 0.0030|
|openbookqa    |      1|none  |     5|acc            |   0.1400|±  | 0.0155|
|              |       |none  |     5|acc_norm       |   0.2200|±  | 0.0185|
|piqa          |      1|none  |     5|acc            |   0.5892|±  | 0.0115|
|              |       |none  |     5|acc_norm       |   0.5854|±  | 0.0115|
|sciq          |      1|none  |     5|acc            |   0.5100|±  | 0.0158|
|              |       |none  |     5|acc_norm       |   0.6020|±  | 0.0155|
|wikitext      |      2|none  |     5|word_perplexity|  87.3261|±  |N/A    |
|              |       |none  |     5|byte_perplexity|   2.3068|±  |N/A    |
|              |       |none  |     5|bits_per_byte  |   1.2059|±  |N/A    |
|winogrande    |      1|none  |     5|acc            |   0.5178|±  | 0.0140|